Effects and Atmospheric Processes of Disaster Weather in the Context of Global Climate Change DOI Open Access
Shenming Fu, Wang Bo

Sustainability, Год журнала: 2025, Номер 17(5), С. 2039 - 2039

Опубликована: Фев. 27, 2025

In recent years, the rapid intensification of global warming has led to significant deterioration and disruption natural environment [...]

Язык: Английский

Hydroclimate volatility on a warming Earth DOI Creative Commons
Daniel L. Swain, Andreas F. Prein, John T. Abatzoglou

и другие.

Nature Reviews Earth & Environment, Год журнала: 2025, Номер 6(1), С. 35 - 50

Опубликована: Янв. 9, 2025

Язык: Английский

Процитировано

17

Rainfall‐Driven Extreme Snowmelt Will Increase in the Tianshan and Pamir Regions Under Future Climate Projection DOI Creative Commons
Tao Yang, Xi Chen,

Rafiq Hamdi

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2025, Номер 130(1)

Опубликована: Янв. 2, 2025

Abstract Snowmelt and related extreme events can have profound natural societal impacts. However, the studies on projected changes in snow‐related extremes across Tianshan Mountains (TS) Pamir regions been underexplored. Utilizing regional climate model downscaling bias‐corrected CMIP6 data, this study examined snowmelt water available for runoff (SM ROS , rainfall plus snowmelt) during cold seasons these historical (1994–2014) future (2040–2060) periods under shared socioeconomic pathway (SSP) scenarios (SSP245 SSP585). The results demonstrated that accumulated was to rise by 17.98% 20.36%, whereas SM could increase 26.97% 28.95%, respectively, SSP245 SSP585 scenarios. Despite relatively minimal snowmelt, magnitude of daily maximum (10‐year return level) 28.04 mm expected 15.32% 15.31% scenarios, especially western TS exceeding 26%. Meanwhile, areas with a 50 over 13.5%. A notable its area occupation high intensity highlighted an increased risk rainfall‐driven events. absolute snowfall frequent snow‐rain phase transitions season warming (SSP245: 2.19°C SSP585: 2.22°C) benefits high‐intensity rain‐on‐snow events, leading augmentation. findings emphasize significant role rainfall‐trigger exacerbating climate.

Язык: Английский

Процитировано

3

A Performance Comparison Study on Climate Prediction in Weifang City Using Different Deep Learning Models DOI Open Access
Qingchun Guo,

Zhenfang He,

Zhaosheng Wang

и другие.

Water, Год журнала: 2024, Номер 16(19), С. 2870 - 2870

Опубликована: Окт. 9, 2024

Climate change affects the water cycle, resource management, and sustainable socio-economic development. In order to accurately predict climate in Weifang City, China, this study utilizes multiple data-driven deep learning models. The data for 73 years include monthly average air temperature (MAAT), minimum (MAMINAT), maximum (MAMAXAT), total precipitation (MP). different models artificial neural network (ANN), recurrent NN (RNN), gate unit (GRU), long short-term memory (LSTM), convolutional (CNN), hybrid CNN-GRU, CNN-LSTM, CNN-LSTM-GRU. CNN-LSTM-GRU MAAT prediction is best-performing model compared other with highest correlation coefficient (R = 0.9879) lowest root mean square error (RMSE 1.5347) absolute (MAE 1.1830). These results indicate that method a suitable model. This can also be used surface modeling. will help flood control management.

Язык: Английский

Процитировано

10

Human-induced N-P imbalances will aggravate GHG emissions from lakes and reservoirs under persisting eutrophication DOI
Wei Yu,

F. Liu,

X. Jiao

и другие.

Water Research, Год журнала: 2025, Номер 276, С. 123240 - 123240

Опубликована: Фев. 2, 2025

Язык: Английский

Процитировано

1

Water limitation as a driver of species richness decline in global grasslands under nutrient addition DOI
Hailing Li, Josep Peñuelas, Scott L. Collins

и другие.

Plant and Soil, Год журнала: 2025, Номер unknown

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

1

The future extent of the Anthropocene epoch: A synthesis DOI Creative Commons
Colin Summerhayes, Jan Zalasiewicz, Martin J. Head

и другие.

Global and Planetary Change, Год журнала: 2024, Номер unknown, С. 104568 - 104568

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

5

From Part to Whole: Scale-Dependence Habitat Selection by Snow Leopards (Panthera Uncia) DOI
Yizhu Wang, Mingxin Liu, Dexi Zhang

и другие.

Опубликована: Янв. 1, 2025

Snow leopards (Panthera uncia) are regarded as the most charismatic apex predator in alpine Asia, yet their populations under serious threat from human activities and habitat fragmentation. Ensuring effectiveness of current protected areas is critical for conservation, which necessitates a comprehensive understanding selection patterns at different spatial scales. Here, we conducted five-year camera trap survey snow Qilian Mountains used multi-scale modelling to investigate connectivity. Our results revealed scale-dependence leopard selection. We found that smaller scales, prey resource topographic variables were main factors determining leopards. Particularly, distribution probability primarily determined overall small scale. At larger however, there was stronger correlation between climate well impacts. The scale-optimized multivariate models indicated significant gaps protecting core habitats ensuring landscape More than 50% projected patches not included areas. Areas with highest number (Subei County) corridors (Tianjun also had least half area outside study provides insights conservation planning suggests prioritizing previously overlooked essential corridors.

Язык: Английский

Процитировано

0

Global drought-flood abrupt alternation: Spatiotemporal patterns, drivers, and projections DOI
Zeqiang Chen, Xinghao Li, Xiang Zhang

и другие.

The Innovation Geoscience, Год журнала: 2025, Номер unknown, С. 100113 - 100113

Опубликована: Янв. 1, 2025

<p>The spatiotemporal patterns and driving factors of drought-flood abrupt alternations (DFAA) have been investigated across several regional watershed scales; however, comprehensive examination at the global scale is lacking. Here, we employed long period change index (LDFAI), derived from an ensemble 40 output datasets eight Coupled Model Intercomparison Project phase 6 (CMIP6) models, to assess patterns, drivers, future projections DFAA. The results indicate that DFAA are influenced by various anthropogenic forcings, greenhouse gas emissions exert most significant impact. changes in intensity (1950–2014), attributed natural forcing (NAT), aerosols (AER), (GHG) forcing, accounted for 5.65%, 14.57%, 33.55%, respectively. rates under shared socioeconomic pathways (SSPs) 2014 <styled-content style-type="number">2100</styled-content> were estimated be 21.73% (SSP1-2.6), 45.37% (SSP2-4.5), 63.1% (SSP3-7.0), 69.51% (SSP5-8.5). This means high radiative rivalry fossil-fuel development models will lead a increase These findings can aid adaptive policies related DFAA.</p>

Язык: Английский

Процитировано

0

Coral-derived seasonal seawater δ18O records from the Northern South China Sea: Hydroclimatic insights into the Medieval Climate Anomaly and Little Ice Age DOI

Huimin Guo,

Xuefei Chen, Yangrui Guo

и другие.

Global and Planetary Change, Год журнала: 2025, Номер unknown, С. 104718 - 104718

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Has global warming already increased precipitation variability and disaster risk in past century? DOI
Huijun Wang

Science China Earth Sciences, Год журнала: 2025, Номер unknown

Опубликована: Янв. 9, 2025

Язык: Английский

Процитировано

0